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Pseudomonas aeruginosa core metabolism exerts a widespread growth-independent control on virulence

TitlePseudomonas aeruginosa core metabolism exerts a widespread growth-independent control on virulence
Publication TypePreprint
Year of Publication2019
AuthorsPanayidou, Stavria, Kaliopi Georgiades, Theodoulakis Christofi, Stella Tamana, V. J. Promponas, and Yiorgos Apidianakis

Bacterial virulence may rely on secondary metabolism, but core metabolism genes are assumed to be necessary primarily for bacterial growth. To assess this assumption, we correlated the genome, the transcriptome and the pathogenicity of 30 fully sequenced Pseudomonas strains using two Drosophila and one mouse infection assay. In accordance with previous studies gene presence-absence does not explain differences in virulence among P. aeruginosa strains, but merely between P. aeruginosa and other Pseudomonas species. Similarly, classical gene expression analysis of highly vs. lowly pathogenic P. aeruginosa strains identifies many virulence factors, and only a few metabolism genes related to virulence. Nevertheless, assessing the virulence of 553 core metabolic and 95 random non-metabolic gene mutants of P. aeruginosa PA14, we found 16.5% of the core metabolic and 8.5% of the non-metabolic genes to be necessary for full virulence. Strikingly, 11.8% of the core metabolism genes exhibit defects in virulence that cannot be attributed to auxotrophy. The compromised in virulence metabolic gene mutants were mapped in multiple pathways and exhibited further defects in acute virulence phenotypes and in a mouse lung infection model. Functional transcriptomics re-analysis of core metabolism at the pathway level, reveals amino-acid, succinate, citramalate, and chorismate biosynthesis and beta-oxidation as important for full virulence and expression of these pathways indicative of virulence in various strains. Thus, P. aeruginosa virulence variation, which to this point remains unpredictably combinatorial at the gene level, can be dissected at the pathway level via combinatorial trancriptome and functional core metabolism analysis.


by Dr. Radut.